Research on artificial intelligence in the last two decades has greatly improved performance of both manufacturing and service systems. Currently, there is a dire need for anarticle that presents a holistic literature survey of worldwide, theoretical frameworks andpractical experiences in the field of artificial intelligence. This paper reports the state-ofthe-art on artificial intelligence in an integrated, concise, and elegantly distilled manner toshow the experiences in the field. In particular, this paper provides a broad review of recentdevelopments within the field of artificial intelligence (AI) and its applications. The work istargeted at new entrants to the artificial intelligence field. It also reminds the experiencedresearchers about some of the issue they have known.
A Literature Review on Articial Intelligence 555 domains to assist human in monitoring team behaviour. The credit of the approach lies in that it customises monitoring behaviour for each specic task, plan and situation, as well as for user preferences. 3.3. Applications of AI in general The study by Franntz (2003) is an example in this respect. The focus is the use of AI as a framework for understanding intuition. His research shows how the overlaps in Herbert Simons work and especially his work on AI aected his view towards intuition. Hebert Simon made overlapping substantive contributions to the elds of economics, psychology, cognitive science, AI, decision theory, and organisation theory. Simons work was motivated by the belief that the human mind, human thinking, decision-making in man, and human creativity need to be mysterious. It was after he helped create thinking machines that Simon came to understand human intuition
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In doing so he showed that intuition need not be associated with magic and mysticism, and that it is complementary with analytical
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A related work to the work of Franntz (2003) is the work presented by Alai (2004). His work centers on whether scientic discovery is a rational and logical process. If it is, according to the AI hypothesis, it should be possible to write computer programs able to discover laws or theories; and if such programs were written, this would denitely prove the existence of logic of discovery. However, a program written by a Simon led group according to this line of reasoning proved abortive. The program was able to infer famous laws of physics and chemistry; but having found no new law, it could not be exactly called a discovery program. The programs written in the Turning tradition, instead, produced new and useful empirical generalisation, but no theoretical discovery. Thus failing to move the logical character of the most signicant kind of discoveries.
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A new cognitivist and connectionist approach by Holland, Holy oak, Nisbett and Thagard, hooks more promisingly. A study of their proposals helps to understand the complex character of discovery processes, the abandonment of belief in the logic of discovery by logical positivists and the necessity of a realist interpretation of scientic research. Similarly, Franklin (2003) deals with the representation of context with ideas drawn from AI. To move beyond vague platitudes about the importance of a context in legal reasoning or natural language understanding, one must take account of ideas from i i i i i i M19N41 2008/11/5 17:14 page 556 #22 556 International Journal of Information and Management Sciences, Vol. 19, No. 4, December, 2008 AI on how to represent context formally. Work on topics like prior probabilities, the
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